Pulmonology

Environmentally sustainable UV spectrophotometric-chemometric approach for simultaneous determination of budesonide, glycopyrrolate, and formoterol.

This study introduces a sustainable UV-spectrophotometric platform for the simultaneous and individual determination of budesonide (BUD), glycopyrrolate (GLY), and formoterol fumarate (FOM) in pharmaceutical inhalers. Current chromatographic approaches for this triple therapy rely on toxic solvents and complex procedures, limiting their suitability for routine pharmaceutical analysis. The proposed...

Artificial Intelligence-Driven Three-Dimensional Reconstruction in Lung Cancer Surgery: Current Status and Future Perspectives.

BACKGROUND: Three-dimensional (3D) reconstruction is an important adjunct in lung cancer surgery for visualizing pulmonary anatomy, supporting preoperative planning, and improving operative precision. Recent advances in artificial intelligence (AI) have accelerated modeling and expanded clinical and educational applications. This review summarizes current evidence and future directions of AI-drive...

Prediction model for deep vein thrombosis stability based on multiple machine learning methods.

BackgroundThis study aimed to develop multiple machine learning (ML) models to predict DVT stability based on clinical and computed tomography (CT) te...

Prediction of SARS-CoV-2 transmission dynamics based on population-level cycle threshold values: An epidemic transmission and machine learning modeling study.

Polymerase chain reaction (PCR) cycle threshold (Ct) values can be used to estimate the viral burden of Severe Acute Respiratory Syndrome Coronavirus ...

Clinical validation of perfusion imaging with pulmonary function test data using Voronoi-based discretization.

Accurate lung function assessment is essential for diagnosing and managing diseases like COPD, pulmonary emboli, and lung cancer. Single-photon emissi...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

Estimating the odds ratio from the output scores of machine learning models: possibilities and limitations.

Estimation of exposure-response association is central to epidemiologic research. Although the advantages of machine learning (ML) techniques for mode...

Fuzzy logic in respiratory medicine: a systematic review of predictive and diagnostic applications.

BACKGROUND: There is increasing interest in the use of artificial intelligence (AI) to assist with respiratory diagnosis and risk prediction. Fuzzy lo...

Breathomics Analysis for Early Diagnosis of Lung Cancer Based on PTR-TOF MS: A Large Sample Size Cross-Sectional Study.

INTRODUCTION: Lung cancer remains a leading cause of cancer mortality globally, emphasising the critical need for non-invasive and cost-effective earl...

In-hospital testing of NIVPredict - an AI tool for early prediction of non-invasive ventilation outcome in acute respiratory failure.

Discrimination between Mycobacterium tuberculosis and Mycobacterium bovis using Fourier transform infrared spectroscopy.

Zoonotic tuberculosis (TB) caused by Mycobacterium bovis (Mbo) is a neglected disease that hinders efforts to eradicate human tuberculosis. Developing...

Personalized sepsis mortality prediction: An interpretable machine learning nomogram.

PURPOSE: Sepsis remains a major cause of mortality in ICU patients, requiring accurate prognostic tools for optimal management. This study aimed to de...

Compound Dry-Hot Events Intensify Widespread Lake Deoxygenation in China.

Lake deoxygenation, driven by climatic warming and anthropogenic influences, threatens aquatic ecosystems. As climate change intensifies, compound dry...

A multi-level segmentation-guided diffusion model for streak artifact reduction in routine non-contrast chest CT.

Streak artifacts in non-contrast computed tomography (NCCT) can obscure anatomical details and even confuse radiologic signs. Existing methods for art...

Feasibility of BMI-based sub-milliSievert low-dose CT in individualized detection of lung nodules.

OBJECTIVES: To evaluate the performance of a body mass index (BMI)-based sub-milliSievert low-dose CT (LDCT) protocol with multiple reconstruction alg...

Clinically applicable deep learning model for segmentation of the mandibular bone and inferior alveolar canal in CBCT cross-sectional images.

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunotherapy is heterogeneous. Machine learning can integrat...

Electrochemical biosensors for Calreticulin in lung Cancer.

Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers. Of t...

A machine learning model to identify pulmonary embolism in patients admitted to intensive care.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of preventable death, yet statistical prediction models have shown inconsistent validity. Our p...